Alternativas de clasificación en poblaciones multivariadas
Classification alternatives in multivariate populations
Abstract (en)
Given the importance, in the last years, of the classification topic and the study yourself have been developed, in this article we compare the efficiency of the classifiers Support Vector Machines (SVM), Fuzzy Classifier (FC), Logistic Regression (LR) and Lineal Discriminate Analysis (LDA), using Multivariate Normal Distribution (MND), Multivariate Skew Normal Distribution (MSND) and Multivariate t Distribution (MTD) for different variables number by means of a simulation study. The best classifier is selected based on your efficiency in terms of the False Discovery Rate (TCE).
Abstract (es)
Dada la importancia del tema de clasificación y los estudios que consigo se han desarrollado, en este artículo se compara, vía simulación, la eficiencia de los clasificadores Máquinas de Soporte Vectorial (SVM), Clasificador Fuzzy (FC), Regresión Logística (LR) y Análisis Discriminante Lineal (LDA), en datos provenientes de las distribuciones Normal Multivariada (MND), Skew Normal Multivariada (MSND) y t Multivariada (MTD), para diferentes números de variables. El mejor clasificador se selecciona de acuerdo con su eficiencia en términos de la tasa de clasificación errónea (TCE).
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